I am building a full-scale algorithmic trading platform and need an experienced developer to take it from concept to production. The core of the system will execute three distinct strategies—scalping, day trading, and swing trading—running side-by-side from a single codebase. The app must pull real-time market data and place live orders across all major asset classes, so please factor in direct integration with: • Stock market APIs • Cryptocurrency exchanges • Forex market feeds Key expectations • Low-latency data capture with WebSocket or equivalent streaming. • Strategy engine that can be toggled per asset, with configurable parameters and risk limits. • Unified order-routing layer capable of handling spot, margin, and conditional orders. • Historical data storage and a back-testing module so I can replay any period and validate results before pushing new logic live. • Responsive dashboard showing P&L, open positions, key metrics, and real-time logs. Deliverables 1. Source code and build instructions. 2. A deployed MVP connected to at least one live venue in each asset class. 3. Tests proving correct execution for each strategy type. 4. Brief user manual walking through setup, parameter tuning, and strategy deployment. Acceptance criteria • Round-trip latency from signal to order acknowledgment under 1 ms on a standard cloud instance. • Back-test results within 0.005 % variance of live forward-test over a 24-hour monitoring window. • No unhandled exceptions during a 48-hour continuous stress test with simultaneous strategy execution. Preferred stack is Python (FastAPI, Pandas, NumPy) on the back end with a lightweight React or Vue front end, but I am open to alternatives if you can justify performance or maintenance gains. If you have demonstrable experience in multi-asset trading systems, let’s move ahead; I’m ready to review your approach and timeline.